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Record W2460385892 · doi:10.1088/0026-1394/53/1a/01008

Final Report. Supplementary comparison of 50/60 Hz energy SIM.EM-S7

2016· article· en· W2460385892 on OpenAlexaff
R. Carranza, S. Campos, A Castruita, Thomas L. Nelson, A.M.L. Ribeiro, Euigeon So, Andrea Spaggiari, Daniel Slomovitz, D Izquierdo, Henry Postigo, Humberto González‐Díaz, Horacio Buitrón Sánchez, Julio Gonzalez, Rodrigo Resende Ramos, A Zipaquira

Bibliographic record

VenueMetrologia · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMutual recognitionEnergy (signal processing)Computer scienceStatisticsKey (lock)MathematicsData miningDatabaseComputer security

Abstract

fetched live from OpenAlex

From 2010 to 2012, a key comparison of energy standards at 50/60 Hz was conducted in the SIM region. The comparison included measurements of active and reactive energy at three frequencies, aiming at providing support to high accuracy measurement needs of reactive energy. This work presents the results of the SIM.EM-S7 supplementary comparison. Main text To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ . The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.327
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3270.153

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.307
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

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